《R语言与统计分析》-参数估计

parcaf

于 2022-10-21 17:37:58 发布

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本文链接：https://blog.youkuaiyun.com/parcaf/article/details/127450834

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####极大似然估计####
#一维参数估计
optimize(f, interval, ..., lower = min(interval), upper = max(interval),
         maximum = FALSE,
         tol = .Machine$double.eps^0.25)
#f是似然函数，interval是参数的范围，lower/upper是参数的下界/上界，
#maximum = FALSE是求最小值，求极大似然估计时设置maximum = T
#tol = .Machine$double.eps^0.25为求值的精确度

#多维参数估计
nlm(f, p, ..., hessian = FALSE, typsize = rep(1, length(p)),
    fscale = 1, print.level = 0, ndigit = 12, gradtol = 1e-6,
    stepmax = max(1000 * sqrt(sum((p/typsize)^2)), 1000),
    steptol = 1e-6, iterlim = 100, check.analyticals = TRUE)

optim(par, fn, gr = NULL, ...,
      method = c("Nelder-Mead", "BFGS", "CG", "L-BFGS-B", "SANN",
                 "Brent"),
      lower = -Inf, upper = Inf,
      control = list(), hessian = FALSE)